International Journal of Computer Science, Information Technology and Applications

Aims & Scope

International Journal of Computer Science, Information Technology and Applications (IJCSITA) is a highly selective peer-reviewed publication covering artificial intelligence, network cryptography, distributed databases, machine learning paradigms, human-computer interfaces, cyber-physical architectures, cloud systems, and quantum algorithms. The journal focuses on practical computational systems and technological integrations that solve complex industrial and societal problems.

Editorial Board

DATI

EDITOR-IN-CHIEF

Dr. Alan Turing III

Stanford University, USA

PSRJ

ASSOCIATE EDITOR

Prof. Srinivasa Ramanujan Jr.

Indian Institute of Technology (IIT) Madras, India

EDITORIAL BOARD MEMBERS

DEP

Dr. Elena Petrova

Lomonosov Moscow State University, Russia

PWL

Prof. William Lee

Tsinghua University, China

DAP

Dr. Arthur Pendelton

Cambridge University, UK

Volume 1, Issue 1 (2026)

Latest published peer-reviewed research papers

✓ CALL FOR PAPERS

Volume 1 · Issue 1 · Pages 1-18DOI: 10.5281/ijcsita.2026.0101

Post-Quantum Cryptographic Protocols for Securing Smart Contracts in Decentralized Web3 Systems

Dr. Alan Turing III, Prof. Srinivasa Ramanujan Jr.

VIEW ABSTRACT

With rapid advancements in quantum computing, widely used public-key encryption schemes face potential compromises. This paper proposes a post-quantum cryptographic protocol using lattice-based algorithms to secure distributed smart contracts. We evaluate the transaction execution speeds and gas consumption of our protocol on a simulated decentralized virtual machine, demonstrating a solid security profile under minimal compute overhead.

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Volume 1 · Issue 1 · Pages 19-33DOI: 10.5281/ijcsita.2026.0102

Federated Learning for Privacy-Preserving Diagnostic Imaging across Global Hospital Alliances

Dr. Elena Petrova, Prof. William Lee

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Deep learning models require massive consolidated datasets, raising severe patient privacy concerns when clinical data is shared across institutions. We present a federated learning architecture that allows multiple international hospitals to collaboratively train a lung nodule detection model without ever sharing raw diagnostic images. The federated model achieved an 94.2% sensitivity rate, matching the accuracy of centralized training models.

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Volume 1 · Issue 1 · Pages 34-48DOI: 10.5281/ijcsita.2026.0103

Ultra-Low Latency Edge Computing Orchestration for Autonomous Drone Swarms in Dense Cities

Dr. Arthur Pendelton, Dr. Kenji Sato

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Coordinating unmanned aerial vehicle (UAV) swarms inside tight city corridors requires ultra-low latency compute resources for collision avoidance. This research implements a localized edge computing architecture that dynamically distributes computing tasks among drone members and municipal 5G edge nodes. Real-world flight trials confirm that our task-allocation algorithm maintains latency below 4.5 milliseconds under high wind disturbances.

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We are actively recruiting distinguished scholars, researchers, and peer-reviewers for IJCSITA. Share your academic expertise and fast-track your career.

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Author Guidelines

•
Format: Word doc (.docx) matching standard double-column JATS.
•
Workflow: Systematic peer-review with a 14-day rapid timeline.
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Licensing: Creative Commons CC BY 4.0 Open Access agreement.

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Indexing & Metadata

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